Triple

T15356201
Position Surface form Disambiguated ID Type / Status
Subject Lego Education E367172 entity
Predicate headquartersLocation P62 FINISHED
Object Billund, Denmark E367160 NE FINISHED

How this triple was built (2 steps)

Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.

NER Named-entity recognition gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Billund, Denmark | Statement: [Lego Education, headquartersLocation, Billund, Denmark]
NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07
Target entity: Billund, Denmark
Context triple: [Lego Education, headquartersLocation, Billund, Denmark]
  • A. Billund, Denmark chosen
    Billund, Denmark is a small Danish town best known as the birthplace of LEGO and home to the original LEGOLAND theme park.
  • B. Farum, Denmark
    Farum, Denmark is a suburban town in Furesø Municipality on the island of Zealand, known for its residential character and proximity to Copenhagen.
  • C. Karup, Denmark
    Karup, Denmark is a village in central Jutland best known as a major military hub and home to the primary air base of the Royal Danish Air Force.
  • D. Hammelev, Denmark
    Hammelev, Denmark is a small Danish village best known as the birthplace of the early 20th-century painter and illustrator Gerda Wegener.
  • E. Aabenraa, Denmark
    Aabenraa, Denmark is a coastal town in Southern Jutland near the German border, known for its historic harbor, maritime heritage, and role as a regional commercial center.
  • F. None of above.
  • G. Unsure - the case is ambiguous/there is not enough information to decide.

Provenance (3 batches)

The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.

Step Stage Batch ID Status When
creating Elicitation batch_69d85a1483788190ad93c2748e8af34b completed April 10, 2026, 2:01 a.m.
NER Named-entity recognition batch_69e03e2c00648190ae2325e1ee58dcfd completed April 16, 2026, 1:41 a.m.
NED1 Entity disambiguation (via context triple) batch_69ff02012fa48190a108f1ca710ffb15 completed May 9, 2026, 9:44 a.m.
Created at: April 10, 2026, 3:18 a.m.